BC-Bench is a benchmark for measuring coding agents on real-world Microsoft Business Central development tasks written in AL. It helps compare models and agent configurations using reproducible evaluation data.
Borrowing it
Nothing to install: this file belongs to microsoft/BC-Bench. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/BC-Bench/main/.github/skills/update-agent-harness/SKILL.mdgit clone --depth 1 https://github.com/microsoft/BC-BenchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/microsoft/bc-bench/update-agent-harness)<a href="https://agentmods.dev/skills/microsoft/bc-bench/update-agent-harness"><img src="https://agentmods.dev/badge/skills/microsoft/bc-bench/update-agent-harness/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/microsoft/bc-bench/update-agent-harness"><img src="https://agentmods.dev/badge/skills/microsoft/bc-bench/update-agent-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.00745 |
| Opus 5.5 | $0.00023 | $0.00298 |
| Sonnet 5.5 | $0.00012 | $0.00149 |
| Haiku 4.5 | $0.00006 | $0.00075 |
Grade A, and why
update-agent-harness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Update Agent Harness
Treat harness updates as benchmark changes. Work manually; do not create workflows, branches, pull requests, tags, or releases unless explicitly asked.
Workflow
- Scope: Check
git status, identify the current pin in.github/actions/install-agent-harnesses/action.yml, and search for all version, model, and default references. Use the latest stable GitHub release unless the user names another version. - Research: Read every intervening first-party GitHub release note. Assume the selected stable release is available on npm; do not gate the update on npm publication metadata or change the installation method. Compare changes against BC-Bench's flags, authentication, prompt mode, exit behavior, sandboxing, MCP/LSP/hooks/plugins, output parsing, debug logs, and model IDs. Resolve required compatibility changes before bumping the pin.
- Curate models: Availability is only a candidate signal. Include models that add a frontier baseline, distinct provider/family, useful cost or speed tier, stable successor, or specific experiment. Exclude superseded, redundant, preview/unstable, unverified, or low-value models. Prefer one representative per role.
- Edit: Change only the version in the existing workflow/action npm install command; do not change how the harness is installed. Update required compatibility code, synchronize curated models across the Python
Literal, workflow choices, command defaults, and judge configuration, then search for stale references. Harness or model changes normally require a minor version bump inpyproject.toml; followCONTRIBUTING.mdfor exceptions. - Validate and report: Verify the installed version and flags, run focused harness tests and
uv run pre-commit run --all-files, and run the full suite when compatibility code changed. A test evaluation using the evaluation identity is required before a full run; hand it off when credentials or infrastructure are unavailable. Report version changes, model decisions, release-note impacts, checks run, and remaining risks.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 40 lines · 58 tokens per session scan A b6a8586c25f9
update-agent-harness is a skill published in the GitHub repository microsoft/BC-Bench (58 stars, last pushed today), licensed MIT. It adds 58 tokens to every session and 745 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
skill-agent-task-patterns
Agent SDK task integration patterns for Business Central. Triggers on: Agent Task Builder, Agent Task Message Builder, Public API, AssignTask, ExternalId, agent session detection, BindSubscription, TryFunction agent task, multi-turn agent conversation, agent attachment, task lifecycle management, OnPrem-only methods…
skill-agent-toolkit
Build, configure, and integrate Business Central agents using the AI Development Toolkit and Agent SDK. Triggers on Agent SDK, Agent Metadata Provider, IAgentFactory, IAgentMetadata, IAgentTaskExecution, ConfigurationDialog, Agent Task Builder, Agent Session, Copilot Capability, agent instructions, or agent setup in…
skill-testing
AL test development patterns for Business Central. Use when creating test codeunits, writing Given/When/Then test procedures, using Library Assert, configuring test projects, or implementing TDD workflows.
skill-api
AL API development patterns for Business Central. Use when creating OData/REST API pages, HttpClient integrations, webhook implementations, or any external system integration via API.
skill-copilot
AL Copilot capability development for Business Central. Use when implementing PromptDialog pages, AI generation features, or integrating with the Copilot toolkit.
skill-migrate
AL version migration for Business Central. Use when upgrading extensions between BC versions, handling breaking changes, or implementing rollback strategies.